Architect / Data Modeler- Senior Manager

Overview

Lead architecture and data modeling work within the Cloud Engineering, Data & Analytics practice, supporting Data Modernisation efforts that shape how data is structured, governed, and used across client priorities.

What you'll do

• Lead data architecture and data modeling efforts across cloud-based and modernized data environments
• Design conceptual, logical, and physical data models that support analytics, reporting, and application use cases
• Translate business and technical requirements into scalable data structures, mappings, and transformation patterns
• Guide data warehouse, data lake, and pipeline design across platforms such as Snowflake, Databricks, Azure Data Factory, and AWS
• Review data quality, validation logic, and performance tuning approaches to improve reliability and query efficiency
• Advise client stakeholders on data strategy, modernization approaches, and architecture tradeoffs across complex initiatives
• Coordinate delivery across data engineering, platform, and product teams to move architecture decisions from design into implementation
• Apply database management, indexing, optimization, and security concepts to support resilient data platforms
• Identify issues in source-to-target design, data integration, and transformation flow, and direct corrective actions
• Coach team members on modeling standards, technical design decisions, and delivery practices across multiple workstreams
• Implement business and IT data requirements through new data strategies and designs across relational, dimensional, and NoSQL platforms and data tools (reporting, visualization)
• Lead the design, development, and implementation of insurance data models supporting interoperability and analytics across Policy Center, Billing Center and Claim Center
• Advise and collaborate closely with engineering, product, and clinical teams to ensure technical solutions meet regulatory, operational, and user requirements
• Understand and translate business needs into data models supporting long-term solutions
• Create logical and physical data models using best practices to ensure high data quality and reduced redundancy
• Develop best practices for standard naming conventions and coding practices to ensure consistency of data models
• Perform reverse engineering of physical data models from databases and SQL scripts
• Evaluate data models and physical databases for variances and discrepancies
• Validate business data objects for accuracy and completeness
• Analyze data-related system integration challenges and propose appropriate solutions
• Identify the architecture, infrastructure, and interfaces to data sources, tools supporting automated data loads, security concerns, analytic models, and data visualization
• Work with business and solution teams to implement data strategies, build data flows, and develop conceptual/logical/physical data models
• Work proactively and independently to address project requirements and articulate issues/challenges to reduce project delivery risks
• Design end-to-end data and analytics solutions using cloud technologies (AWS S3, Spark, EMR, Databricks, MPP databases, Redshift/Snowflake), from ingestion to transformation to consumption, including API delivery or similar knowledge in alternate cloud services
• Analyze data warehouse performance issues and determine resolutions using various methods and techniques

What you'll need

• At least a Bachelor's degree
• At least 12+ years of experience
• 12+ years of experience in data modeling, responsible for developing conceptual, logical, and physical data models and implementing RDBMS, operational data store (ODS), data marts, and data lakes on target platforms (SQL/NoSQL)
• Oral and written proficiency in English
• Deep understanding of insurance domain knowledge
• Well versed in data modeling tools such as ER/Studio, Erwin Data Modeler, Data Vault, Toad Data Modeler etc.
• Hands-on experience working in cloud technologies – AWS/Azure/GCP
• End-to-end data and analytics solutions design experience using cloud technologies (AWS S3, Spark, EMR, Databricks, MPP databases, Redshift/Snowflake), from ingestion to transformation to consumption, including API delivery or similar knowledge in alternate cloud services
• Strong skills in SQL and SQL procedure builds
• Strong skills in analyzing data warehouse performance issues and resolutions using various methods/techniques
• Strong analytical and troubleshooting skills
• Excellent communication skills

Details

• Location: Bangalore
• Job posting end date stated in the ad; travel requirements not specified